Improving NIR Imaging Quality Using 3D Camera for the Detection of Cancer

The primary objective of the SBIR effort proposed herein is to investigate the feasibility of significantly improving the near infrared (NIR) imaging quality by using a novel 3D image device to provide accurate three-dimensional (3D) geometric boundaryconditions in nonlinear reconstruction process.NIR imaging has re-emerged as a promising imaging modality and dramatically improved our ability to localize and quantify tissue structures with light. However, the advanced NIR algorithm requires good knowledge of the boundary geometry of the diffusemedium imaged in order to provide accurate forward models of light propagation within this medium. Original experimental NIR demonstrations for reconstructing absorbers, scatterers and fluorochromes all used phantoms or tissues confined to easily modeledgeometries such as a slab or a cylinder. In recent years several methods have been developed to model photon propagation through diffuse media with complex boundaries using Monte Carlo approaches, finite solutions of the diffusion or transport equation ormore recently analytical methods based on the tangent-plane method. To fully exploit the advantages to these sophisticated algorithms, accurate 3D boundary geometry of the subject has to be extracted in practical, real-time, and in vivo manner.To date, there is no known reported technique for extracting 3D dimensional boundaries with fully automated, accurate and real-time in vivo performance. We propose this SBIR project to address this urgent need. The long-team goal of this research projectis to develop a new optical tomography system that coherently combines the diffuse optical tomographic sensor/light source with real-time precision 3D surface images device so that the boundary geometry of the object to be imaged would be extracted almostsimultaneously as the NIR imaging is performing. The long-team goal of this research project is to develop a new generation optical tomography system that coherently combines the diffuse optical tomographic sensor/light source with real-time precision 3D surface images device so that the boundarygeometry of the object to be imaged would be extracted almost simultaneously as the NIR imaging is performing. Such technology would lead to a set of very useful tools for small animal studies, as well as for the potential clinical use for breast cancerand brain cancer detection.